ESR will work within Philips' Data Science department whose mission is to lead Philips into the Digital era through world-class innovations based on data science. The focus of the department is on applying and advancing the automated methods used to extract new insights/knowledge from data. The department builds on several interconnected competences including machine learning, statistics, probability models, pattern recognition, computer vision, signal processing and data engineering. We use the advances in the aforementioned scientific disciplines, as well as new digital platforms to create innovation for Philips businesses by extracting insights from various sources like health records, sensors, mobile devices, Web, and social networking sites. Next to that, security and privacy are addressed and taken into account already in the design phase of Philips digital propositions. The department plays a crucial role in digital and data intensive research projects using these competences.

OBJECTIVES

In the domains of smart homes and healthcare, the life of people is improved by devices that gather personal data and process it, into relevant health information using third party smart services and technology providers (e.g. cloud and Big Data analytics services). While the use of IoT devices can bring advantages in terms of efficiency, convenience, and costs, their use raises privacy concerns regarding the users and their personal activity data. The sensitive nature of this data and sharing it with a centralized server (e.g. cloud) raise privacy concerns, even if the latter is well protected. These privacy concerns can be addressed by using an end-to-end approach to privacy and data protection and building systems with privacy embedded in the system architecture, while coherently integrating health-specific privacy, security and legal requirements.